textobjdetection

KO | EN

gitlite — search

#javascript #python #ai #machine-learning #deep-learning #linux #docker #nodejs #cli #vue #security #pytorch #mcp #open-source

textobjdetection

(★ 13)

Code for the Human-related Object Detection based on Natural Language Parsing of Image Query Expressions article

textobjdetection 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# textobjdetection
Code for the Human-related Object Detection based on Natural Language Parsing of Image
Query Expressions article

## Project status
[![License](https://img.shields.io/badge/license-MIT-blue.svg)](https://raw.githubusercontent.com/andfoy/textobjdetection/master/LICENSE)

## Dependencies

To execute this, you must have Python 3.6.*, [PyTorch](http://pytorch.org/), [OpenCV](http://opencv.org/), [Numpy](http://www.numpy.org/) and [Matplotlib](https://matplotlib.org/) installed, to accomplish this, we recommend installing the [Anaconda](https://www.continuum.io/downloads) Python distribution and use conda to install the dependencies, as it follows:

```bash
conda install pytorch torchvision cuda80 -c soumith
conda install opencv -c conda-forge
conda install matplotlib numpy
conda install aria2 -c bioconda
pip install visual-genome
```

## Dataset download
You must download the [Visual Genome](http://visualgenome.org/api/v0/api_home.html) dataset, as well the train/val/test split used for our experiments. For this, we provide the ``download_dataset.sh`` bash script, it will take care of the downloads required.

## Pretrained models
Pretrained SSD + LSTM weights are provided as proof of our experimients. They are available at:

* **LSTM Model:** https://s3-sa-east-1.amazonaws.com/textobjdetection/lstm_model.pt
* **SSD Model:** https://s3-sa-east-1.amazonaws.com/textobjdetection/ssd_lang.pt

After downloading the models, they must be uncompressed under the ``weights`` folder.

## Demo
A simple demo is provided as a [Jupyter Notebook](Demo.ipynb), here you can load images and predict bounding boxes given a object query phrase.

![alt tag](https://raw.githubusercontent.com/andfoy/textobjdetection/master/demo/demo2.png)

## Acknowledgements
The SSD multibox detector is based on amdegroot's PyTorch implementation: https://github.com/amdegroot/ssd.pytorch

## Contributions
Any contribution Pull Request will reviewed as part of Open Source initiative. We follow PEP8 and PEP257 guidelines

textobjdetection

textobjdetection 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

textobjdetection

textobjdetection 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README